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CALL FOR PAPERS
Image and Vision Computing Journal (Elsevier)

Special Issue on
Affect Analysis in Continuous Input

http://www.elsevierscitech.com/dronsite/cfp/IVCJ_SI_AffectAnalysisInContinuousInput_CFP.pdf

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Theme and Scope of the Issue
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Human affective behavior is multimodal, continuous and complex. In day-to-day
interactions people naturally communicate subtle affective states by means of language,
vocal intonation, facial expression, hand gesture, head movement, body movement and
posture, and possess a refined mechanism for understanding and interpreting information
conveyed by these behavioral cues. Despite major advances within the affective
computing research field, modeling, sensing, recognizing, interpreting and responding to
such human affective behavior still remains as a challenge for automated systems as
human emotions are complex constructs with fuzzy boundaries and with substantial
individual variations in expression and experience. Thus, a small number of discrete
categories (e.g., happiness and sadness) may not reflect the subtlety and complexity of
the emotions conveyed by such rich sources of information. Therefore, human and
behavioral computing researchers have recently invested increased effort exploring how
to best model, analyze and interpret the subtlety, complexity and continuity (represented
along a continuum) of affective behavior in terms of latent dimensions (e.g., arousal,
power and valence) and appraisals, rather than in terms of a small number of discrete
emotion categories (e.g., happiness, sadness, surprise, disgust, fear and anger).

Therefore, this Special Issue aims to focus on Affect Analysis in Continuous Input and to
attract original articles discussing the issues and the challenges pertinent in sensing,
recognizing and responding to continuous human affective behavior from diverse
communicative cues and modalities.

More specifically, it will bring together research work (i) reviewing the latest
developments in the field, (ii) exploring and proposing novel dynamic pattern recognition
and prediction techniques and multimodal fusion methods, (iii) setting key standards, and
defining future research directions, and (iv) demonstrating the practical use of these
methodologies in various application domains (e.g., interaction with robots, virtual
agents, and games, single and multi-user smart environments, clinical and biomedical
studies, etc.).


Suggested submission topics include, but are by no means limited to:
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• Analysis of human affective behavior in continuous input
- facial expressions
- head movements and gestures
- body postures and gestures
- multiple cues and modalities (e.g., video, speech, non-linguistic
vocalizations, biosignals such as heart, brain, thermal signals, etc.)

• Novel pattern recognition and prediction approaches
- discretized and continuous prediction of affect
- handling the dynamics of affective patterns
- novel recognition and prediction methods
- optimal strategies for fusion
- modeling high inter-subject variation

• Data acquisition and annotation
- (multimodal) naturalistic data sets
- (multimodal) pattern annotation tools
- modeling annotation patterns from multiple raters and reliability

• Applications
- interaction with robots, virtual agents, and games (including tutoring)
- single and multi-user smart environments (e.g., in a car)
- implicit (multimedia) tagging
- clinical and biomedical studies (e.g., autism, depression, pain etc.)


Tentative Dates
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• Full paper due: 15 October 2011 (extended)
• First notification: 1 January 2012
• Revised Manuscript (for second review) due: 1 March 2012
• Acceptance notification: 1 May 2012


Guest Editors
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Hatice Gunes
Imperial College London, UK
Email: h.gunes@imperial.ac.uk

Björn Schuller
Technische Universität München, Germany
Email: schuller@tum.de


Submission Procedure
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Prospective authors should follow the regular guidelines of the Image and Vision
Computing Journal for electronic submission:
(http://ees.elsevier.com/imavis). During submission authors must select the “Special
Issue: Continuous Affect Analysis” when they reach the “Article Type”.